Assessing Band Sensitivity to Atmospheric Radiation Transfer for Space-Based Retrieval of Solar-Induced Chlorophyll Fluorescence

被引:31
|
作者
Liu, Xinjie [1 ,2 ]
Liu, Liangyun [1 ]
机构
[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
基金
中国国家自然科学基金;
关键词
sensitivity analysis; band selection; solar-induced chlorophyll fluorescence; atmospheric radiation transfer; ROTATIONAL-RAMAN-SCATTERING; STRESS DETECTION; PHOTOSYNTHESIS; INSTRUMENT; IMPACT; LEAF;
D O I
10.3390/rs61110656
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In contrast to ground-based solar-induced chlorophyll fluorescence (Fs) detection, the influence of atmospheric radiation transfer is the major difficulty in Fs retrieval from space. In this study, we first simulated top-of-atmosphere (TOA) radiance using FluorMODgui3.1 and MODTRAN5 code. Based on the simulated dataset, we analyzed the sensitivities of five potential Fs retrieval bands (H alpha, K I, Fe, O-2-A, and O-2-B) to different atmospheric transfer parameters, including atmosphere profile, aerosol optical depth (AOD(550)), vertical water vapor column (H2O), vertical ozone column (O-3), solar zenith angle (SZA), view zenith angle (VZA), relative azimuth angle (RAA) and elevation. The results demonstrate that the H alpha, O-2-A and O-2-B bands are the most sensitive to these atmospheric parameters. However, only the O-2-A and O-2-B bands were found to be sensitive to the imaging geometric parameters. When the spectral resolution was sufficient, the K I and Fe bands proved to have the best potential for space-based Fs retrieval given the current available accuracies of atmospheric products, while the O-2-A band was shown to perform better at lower spectral resolutions. The band sensitivity analysis presented here will be useful for band selection and atmospheric correction for space-based Fs retrieval.
引用
收藏
页码:10656 / 10675
页数:20
相关论文
共 50 条
  • [41] Assessing the potential of red solar-induced chlorophyll fluorescence for drought monitoring in different growth stages of winter wheat
    Zhou, Litao
    Lin, Jingyu
    Wu, Jianjun
    Du, Ruohua
    Chen, Meng
    Zhao, Bingyu
    Yang, Rui
    ECOLOGICAL INDICATORS, 2024, 161
  • [42] Assessing bi-directional effects on the diurnal cycle of measured solar-induced chlorophyll fluorescence in crop canopies
    Zhang, Zhaoying
    Zhang, Yongguang
    Zhang, Qian
    Chen, Jing M.
    Porcar-Castell, Albert
    Guanter, Luis
    Wu, Yunfei
    Zhang, Xiaokang
    Wang, Hezhou
    Ding, Dawei
    Li, Zhongyang
    AGRICULTURAL AND FOREST METEOROLOGY, 2020, 295
  • [43] Solar-induced fluorescence of terrestrial chlorophyll derived from the O2-A band of Hyperion hyperspectral images
    Raychaudhuri, Barun
    REMOTE SENSING LETTERS, 2014, 5 (11) : 941 - 950
  • [44] Vegetation Phenology in Permafrost Regions of Northeastern China Based on MODIS and Solar-induced Chlorophyll Fluorescence
    WEN Lixiang
    GUO Meng
    YIN Shuai
    HUANG Shubo
    LI Xingli
    YU Fangbing
    Chinese Geographical Science, 2021, 31 (03) : 459 - 473
  • [45] Vegetation Phenology in Permafrost Regions of Northeastern China Based on MODIS and Solar-induced Chlorophyll Fluorescence
    WEN Lixiang
    GUO Meng
    YIN Shuai
    HUANG Shubo
    LI Xingli
    YU Fangbing
    Chinese Geographical Science , 2021, (03) : 459 - 473
  • [46] A novel composite vegetation index including solar-induced chlorophyll fluorescence for seedling rapeseed net photosynthesis rate retrieval
    Zhang, Jian
    Sun, Bo
    Yang, Chenghai
    Wang, Chunyun
    You, Yunhao
    Zhou, Guangsheng
    Liu, Bin
    Wang, Chufeng
    Kuai, Jie
    Xie, Jing
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2022, 198
  • [47] Solar-induced chlorophyll fluorescence extraction based on heterogeneous light distribution for improving in-situ chlorophyll content estimation
    Zhao, Ruomei
    Tang, Weijie
    An, Lulu
    Qiao, Lang
    Wang, Nan
    Sun, Hong
    Li, Minzan
    Liu, Guohui
    Liu, Yang
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2023, 215
  • [48] A scalable crop yield estimation framework based on remote sensing of solar-induced chlorophyll fluorescence (SIF)
    Kira, Oz
    Wen, Jiaming
    Han, Jimei
    McDonald, Andrew J.
    Barrett, Christopher B.
    Ortiz-Bobea, Ariel
    Liu, Yanyan
    You, Liangzhi
    Mueller, Nathaniel D.
    Sun, Ying
    ENVIRONMENTAL RESEARCH LETTERS, 2024, 19 (04)
  • [49] Downscaling Solar-Induced Chlorophyll Fluorescence Based on Convolutional Neural Network Method to Monitor Agricultural Drought
    Zhang, Zhaoxu
    Xu, Wei
    Qin, Qiming
    Long, Zehao
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 59 (02): : 1012 - 1028
  • [50] Assessing the wavelength-dependent ability of solar-induced chlorophyll fluorescence to estimate the GPP of winter wheat at the canopy level
    Liu, Liangyun
    Liu, Xinjie
    Hu, Jiaochan
    Guan, Linlin
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (15) : 4396 - 4417